OpenRaiser/Intern-Atlas huggingface dataset:
SIFT-based Ear Recognition by Fusion of Detected Keypoints from Color Similarity Slice Regions
Venue: arXiv cs.CV 2010
Year: 2010

Ear biometric is considered as one of the most reliable and invariant biometrics characteristics in line with iris and fingerprint characteristics. In many cases, ear biometrics can be compared with face biometrics regarding many physiological and texture characteristics. In this paper, a robust and efficient ear recognition system is presented, which uses Scale Invariant Feature Transform (SIFT) as feature descriptor for structural representation of ear images. In order to make it more robust to user authentication, only the regions having color probabilities in a certain ranges are considered for invariant SIFT feature extraction, where the K-L divergence is used for keeping color consistency. Ear skin color model is formed by Gaussian mixture model and clustering the ear color pattern using vector quantization. Finally, K-L divergence is applied to the GMM framework for recording the color similarity in the specified ranges by comparing color similarity between a pair of reference model and probe ear images. After segmentation of ear images in some color slice regions, SIFT keypoints are extracted and an augmented vector of extracted SIFT features are created for matching, which is accomplished between a pair of reference model and probe ear images. The proposed technique has been tested on the IITK Ear database and the experimental results show improvements in recognition accuracy while invariant features are extracted from color slice regions to maintain the robustness of the system.
Recognition and translation Arabic-French of Named Entities: case of the Sport places
Venue: arXiv cs.CL 2010
Year: 2010

The recognition of Arabic Named Entities (NE) is a problem in different domains of Natural Language Processing (NLP) like automatic translation. Indeed, NE translation allows the access to multilingual in-formation. This translation doesn't always lead to expected result especially when NE contains a person name. For this reason and in order to ameliorate translation, we can transliterate some part of NE. In this context, we propose a method that integrates translation and transliteration together. We used the linguis-tic NooJ platform that is based on local grammars and transducers. In this paper, we focus on sport domain. We will firstly suggest a refinement of the typological model presented at the MUC Conferences we will describe the integration of an Arabic transliteration module into translation system. Finally, we will detail our method and give the results of the evaluation.
Morphological study of Albanian words, and processing with NooJ
Venue: arXiv cs.CL 2010
Year: 2010

We are developing electronic dictionaries and transducers for the automatic processing of the Albanian Language. We will analyze the words inside a linear segment of text. We will also study the relationship between units of sense and units of form. The composition of words takes different forms in Albanian. We have found that morphemes are frequently concatenated or simply juxtaposed or contracted. The inflected grammar of NooJ allows constructing the dictionaries of flexed forms (declensions or conjugations). The diversity of word structures requires tools to identify words created by simple concatenation, or to treat contractions. The morphological tools of NooJ allow us to create grammatical tools to represent and treat these phenomena. But certain problems exceed the morphological analysis and must be represented by syntactical grammars.
Study of Reconfigurable Mostly Digital Radio for Manet
Venue: arXiv cs.NI 2010
Year: 2010

We introduce the radio reconfigurability thanks to IRUWB mostly digital architecture for MANET context. This particular context implies some constraints on the radio interface such as low cost, low power, small dimensions and simplicity. Here, we propose an implementation of dynamic reconfigurable receiver on ASIC, and FPGA, after having explained the advantages of mostly digital radio for reconfigurability. In this paper, by studying our prototypes, we could prove that reconfigurability is on the contrary with MANET constraints needs. The proposed solution allows data rate, radio range, energy and spectrum occupation reconfigurability.
Performance Analysis of m-retry BEB based DCF under Unsaturated Traffic Condition
Venue: arXiv cs.NI 2010
Year: 2010

The IEEE 802.11 standard offers a cheap and promising solution for small scale wireless networks. Due to the self configuring nature, WLANs do not require large scale infrastructure deployment, and are scalable and easily maintainable which incited its popularity in both literature and industry. In real environment, these networks operate mostly under unsaturated condition. We investigate performance of such a network with m-retry limit BEB based DCF. We consider imperfect channel with provision for power capture. Our method employs a Markov model and represents the most common performance measures in terms of network parameters making the model and mathematical analysis useful in network design and planning. We also explore the effects of packet error, network size, initial contention window, and retry limit on overall performance of WLANs.
FORMT: Form-based Mutation Testing of Logical Specifications
Venue: arXiv cs.SE 2010
Year: 2010

The draft paper defines a system, which is capable of maintaining bases of test cases for logical specifications. The specifications, which are subject to this system are transformed from their original shape in first-order logic to form-based expressions as originally introduced in logics of George Spencer-Brown. The innovation comes from the operations the system provides when injecting faults - so-called mutations - to the specifications. The system presented here applies to logical specifications from areas as different as programming, ontologies or hardware specifications.
Detecting Danger: Applying a Novel Immunological Concept to Intrusion Detection Systems
Venue: arXiv cs.AI 2010
Year: 2010

In recent years computer systems have become increasingly complex and consequently the challenge of protecting these systems has become increasingly difficult. Various techniques have been implemented to counteract the misuse of computer systems in the form of firewalls, anti-virus software and intrusion detection systems. The complexity of networks and dynamic nature of computer systems leaves current methods with significant room for improvement. Computer scientists have recently drawn inspiration from mechanisms found in biological systems and, in the context of computer security, have focused on the human immune system (HIS). The human immune system provides a high level of protection from constant attacks. By examining the precise mechanisms of the human immune system, it is hoped the paradigm will improve the performance of real intrusion detection systems. This paper presents an introduction to recent developments in the field of immunology. It discusses the incorporation of a novel immunological paradigm, Danger Theory, and how this concept is inspiring artificial immune systems (AIS). Applications within the context of computer security are outlined drawing direct reference to the underlying principles of Danger Theory and finally, the current state of intrusion detection systems is discussed and improvements suggested.
Prequential Plug-In Codes that Achieve Optimal Redundancy Rates even if the Model is Wrong
Venue: arXiv cs.IT 2010
Year: 2010

We analyse the prequential plug-in codes relative to one-parameter exponential families M. We show that if data are sampled i.i.d. from some distribution outside M, then the redundancy of any plug-in prequential code grows at rate larger than 1/2 ln(n) in the worst case. This means that plug-in codes, such as the Rissanen-Dawid ML code, may behave inferior to other important universal codes such as the 2-part MDL, Shtarkov and Bayes codes, for which the redundancy is always 1/2 ln(n) + O(1). However, we also show that a slight modification of the ML plug-in code, "almost" in the model, does achieve the optimal redundancy even if the the true distribution is outside M.
Towards the Safe Programming of Wireless Sensor Networks
Venue: arXiv cs.PL 2010
Year: 2010

Sensor networks are rather challenging to deploy, program, and debug. Current programming languages for these platforms suffer from a significant semantic gap between their specifications and underlying implementations. This fact precludes the development of (type-)safe applications, which would potentially simplify the task of programming and debugging deployed networks. In this paper we define a core calculus for programming sensor networks and propose to use it as an assembly language for developing type-safe, high-level programming languages.
A Concurrent Language with a Uniform Treatment of Regions and Locks
Venue: arXiv cs.PL 2010
Year: 2010

A challenge for programming language research is to design and implement multi-threaded low-level languages providing static guarantees for memory safety and freedom from data races. Towards this goal, we present a concurrent language employing safe region-based memory management and hierarchical locking of regions. Both regions and locks are treated uniformly, and the language supports ownership transfer, early deallocation of regions and early release of locks in a safe manner.
Modelling Mobility: A Discrete Revolution
Venue: arXiv cs.DM 2010
Year: 2010

We introduce a new approach to model and analyze \emph{Mobility}. It is fully based on discrete mathematics and yields a class of mobility models, called the \emph{Markov Trace} Model. This model can be seen as the discrete version of the \emph{Random Trip} Model including all variants of the \emph{Random Way-Point} Model \cite{L06}. We derive fundamental properties and \emph{explicit} analytical formulas for the \emph{stationary distributions} yielded by the Markov Trace Model. Such results can be exploited to compute formulas and properties for concrete cases of the Markov Trace Model by just applying counting arguments. We apply the above general results to the discrete version of the \emph{Manhattan Random Way-Point} over a square of bounded size. We get formulas for the total stationary distribution and for two important \emph{conditional} ones: the agent spatial and destination distributions. Our method makes the analysis of complex mobile systems a feasible task. As a further evidence of this important fact, we first model a complex vehicular-mobile system over a set of crossing streets. Several concrete issues are implemented such as parking zones, traffic lights, and variable vehicle speeds. By using a \emph{modular} version of the Markov Trace Model, we get explicit formulas for the stationary distributions yielded by this vehicular-mobile model as well.
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets
Venue: arXiv cs.DB 2010
Year: 2010

As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications. In this work, we address significance in the context of frequent itemset mining. Specifically, we develop a novel methodology to identify a meaningful support threshold s* for a dataset, such that the number of itemsets with support at least s* represents a substantial deviation from what would be expected in a random dataset with the same number of transactions and the same individual item frequencies. These itemsets can then be flagged as statistically significant with a small false discovery rate. We present extensive experimental results to substantiate the effectiveness of our methodology.
A Logical Temporal Relational Data Model
Venue: arXiv cs.DB 2010
Year: 2010

Time is one of the most difficult aspects to handle in real world applications such as database systems. Relational database management systems proposed by Codd offer very little built-in query language support for temporal data management. The model itself incorporates neither the concept of time nor any theory of temporal semantics. Many temporal extensions of the relational model have been proposed and some of them are also implemented. This paper offers a brief introduction to temporal database research. We propose a conceptual model for handling time varying attributes in the relational database model with minimal temporal attributes.
Existence and Global Logarithmic Stability of Impulsive Neural Networks with Time Delay
Venue: arXiv cs.NE 2010
Year: 2010

The stability and convergence of the neural networks are the fundamental characteristics in the Hopfield type networks. Since time delay is ubiquitous in most physical and biological systems, more attention is being made for the delayed neural networks. The inclusion of time delay into a neural model is natural due to the finite transmission time of the interactions. The stability analysis of the neural networks depends on the Lyapunov function and hence it must be constructed for the given system. In this paper we have made an attempt to establish the logarithmic stability of the impulsive delayed neural networks by constructing suitable Lyapunov function.
Significant Interval and Frequent Pattern Discovery in Web Log Data
Venue: arXiv cs.DB 2010
Year: 2010

There is a considerable body of work on sequence mining of Web Log Data. We are using One Pass frequent Episode discovery (or FED) algorithm, takes a different approach than the traditional apriori class of pattern detection algorithms. In this approach significant intervals for each Website are computed first (independently) and these interval used for detecting frequent patterns/Episode and then the Analysis is performed on Significant Intervals and frequent patterns That can be used to forecast the user's behavior using previous trends and this can be also used for advertising purpose. This type of applications predicts the Website interest. In this approach, time-series data are folded over a periodicity (day, week, etc.) Which are used to form the Interval? Significant intervals are discovered from these time points that satisfy the criteria of minimum confidence and maximum interval length specified by the user.
Modified EESM Based Link Adaptation Algorithm for Multimedia Transmission in Multicarrier Systems
Venue: arXiv cs.OH 2010
Year: 2010

The previous link adaptation algorithms on ofdm based systems use equal modulation order for all sub carrier index within a block. For multimedia transmission using ofdm as the modulation technique, unequal constellation is used within one ofdm subcarrier block, a set of subcarriers for audio and another set for video transmissions. A generic model has been shown for such a transmission and link adaptation algorithm has been proposed using EESM (Effective Exponential SNR mapping) method as basic method. Mathematical model has been derived for the channel based on bivariate Gaussian distribution in which the amplitude varies two dimensionally in the same envelope. From the Moment generating function of bivariate distribution, Probability of error has been theoretically derived. Results have been shown for BER performance of an ofdm system using unequal constellation. BER performances have been shown for different values of correlation parameter and fading figure.
Ball-Scale Based Hierarchical Multi-Object Recognition in 3D Medical Images
Venue: arXiv cs.CV 2010
Year: 2010

This paper investigates, using prior shape models and the concept of ball scale (b-scale), ways of automatically recognizing objects in 3D images without performing elaborate searches or optimization. That is, the goal is to place the model in a single shot close to the right pose (position, orientation, and scale) in a given image so that the model boundaries fall in the close vicinity of object boundaries in the image. This is achieved via the following set of key ideas: (a) A semi-automatic way of constructing a multi-object shape model assembly. (b) A novel strategy of encoding, via b-scale, the pose relationship between objects in the training images and their intensity patterns captured in b-scale images. (c) A hierarchical mechanism of positioning the model, in a one-shot way, in a given image from a knowledge of the learnt pose relationship and the b-scale image of the given image to be segmented. The evaluation results on a set of 20 routine clinical abdominal female and male CT data sets indicate the following: (1) Incorporating a large number of objects improves the recognition accuracy dramatically. (2) The recognition algorithm can be thought as a hierarchical framework such that quick replacement of the model assembly is defined as coarse recognition and delineation itself is known as finest recognition. (3) Scale yields useful information about the relationship between the model assembly and any given image such that the recognition results in a placement of the model close to the actual pose without doing any elaborate searches or optimization. (4) Effective object recognition can make delineation most accurate.
Integrating Interval Constraints into Logic Programming
Venue: arXiv cs.PL 2010
Year: 2010

The CLP scheme uses Horn clauses and SLD resolution to generate multiple constraint satisfaction problems (CSPs). The possible CSPs include rational trees (giving Prolog) and numerical algorithms for solving linear equations and linear programs (giving CLP(R)). In this paper we develop a form of CSP for interval constraints. In this way one obtains a logic semantics for the efficient floating-point hardware that is available on most computers. The need for the method arises because in the practice of scheduling and engineering design it is not enough to solve a single CSP. Ideally one should be able to consider thousands of CSPs and efficiently solve them or show them to be unsolvable. This is what CLP/NCSP, the new subscheme of CLP described in this paper is designed to do.
On Functionality of Visibly Pushdown Transducers
Venue: arXiv cs.FL 2010
Year: 2010

Visibly pushdown transducers form a subclass of pushdown transducers that (strictly) extends finite state transducers with a stack. Like visibly pushdown automata, the input symbols determine the stack operations. In this paper, we prove that functionality is decidable in PSpace for visibly pushdown transducers. The proof is done via a pumping argument: if a word with two outputs has a sufficiently large nesting depth, there exists a nested word with two outputs whose nesting depth is strictly smaller. The proof uses technics of word combinatorics. As a consequence of decidability of functionality, we also show that equivalence of functional visibly pushdown transducers is Exptime-Complete.
On Coding for Cooperative Data Exchange
Venue: arXiv cs.IT 2010
Year: 2010

We consider the problem of data exchange by a group of closely-located wireless nodes. In this problem each node holds a set of packets and needs to obtain all the packets held by other nodes. Each of the nodes can broadcast the packets in its possession (or a combination thereof) via a noiseless broadcast channel of capacity one packet per channel use. The goal is to minimize the total number of transmissions needed to satisfy the demands of all the nodes, assuming that they can cooperate with each other and are fully aware of the packet sets available to other nodes. This problem arises in several practical settings, such as peer-to-peer systems and wireless data broadcast. In this paper, we establish upper and lower bounds on the optimal number of transmissions and present an efficient algorithm with provable performance guarantees. The effectiveness of our algorithms is established through numerical simulations.
Deterministic Black-Box Identity Testing $π$-Ordered Algebraic Branching Programs
Venue: arXiv cs.CC 2010
Year: 2010

In this paper we study algebraic branching programs (ABPs) with restrictions on the order and the number of reads of variables in the program. Given a permutation $π$ of $n$ variables, for a $π$-ordered ABP ($π$-OABP), for any directed path $p$ from source to sink, a variable can appear at most once on $p$, and the order in which variables appear on $p$ must respect $π$. An ABP $A$ is said to be of read $r$, if any variable appears at most $r$ times in $A$. Our main result pertains to the identity testing problem. Over any field $F$ and in the black-box model, i.e. given only query access to the polynomial, we have the following result: read $r$ $π$-OABP computable polynomials can be tested in $\DTIME[2^{O(r\log r \cdot \log^2 n \log\log n)}]$. Our next set of results investigates the computational limitations of OABPs. It is shown that any OABP computing the determinant or permanent requires size $Ω(2^n/n)$ and read $Ω(2^n/n^2)$. We give a multilinear polynomial $p$ in $2n+1$ variables over some specifically selected field $G$, such that any OABP computing $p$ must read some variable at least $2^n$ times. We show that the elementary symmetric polynomial of degree $r$ in $n$ variables can be computed by a size $O(rn)$ read $r$ OABP, but not by a read $(r-1)$ OABP, for any $0 < 2r-1 \leq n$. Finally, we give an example of a polynomial $p$ and two variables orders $π\neq π'$, such that $p$ can be computed by a read-once $π$-OABP, but where any $π'$-OABP computing $p$ must read some variable at least $2^n$
Power Control for Maximum Throughput in Spectrum Underlay Cognitive Radio Networks
Venue: arXiv cs.IT 2010
Year: 2010

We investigate power allocation for users in a spectrum underlay cognitive network. Our objective is to find a power control scheme that allocates transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service (QoS) of the primary users greater than a certain minimum limit. Since an optimum solution to our problem is computationally intractable, as the optimization problem is non-convex, we propose an iterative algorithm based on sequential geometric programming, that is proved to converge to at least a local optimum solution. We use the proposed algorithm to show how a spectrum underlay network would achieve higher throughput with secondary users operation than with primary users operating alone. Also, we show via simulations that the loss in primary throughput due to the admission of the secondary users is accompanied by a reduction in the total primary transmit power.
Design of Current Controller for Two Quadrant DC Motor Drive by Using Model Order Reduction Technique
Venue: arXiv cs.OH 2010
Year: 2010

In this paper, design of current controller for a two quadrant DC motor drive was proposed with the help of model order reduction technique. The calculation of current controller gain with some approximations in the conventional design process is replaced by proposed model order reduction method. The model order reduction technique proposed in this paper gives the better controller gain value for the DC motor drive. The proposed model order reduction method is a mixed method, where the numerator polynomial of reduced order model is obtained by using stability equation method and the denominator polynomial is obtained by using some approximation technique preceded in this paper. The designed controllers responses were simulated with the help of MATLAB to show the validity of the proposed method.